Fernando Paolo
Senior Machine Learning Engineer, Research and Innovation
Pasadena, California
Fernando Paolo develops machine learning algorithms for Global Fishing Watch’s analysis of satellite data to investigate human activity at sea and associated environmental change. A strong advocate of open source and open data, Paolo focuses his time on AI-powered object detection systems, using synthetic aperture radar imagery and cloud computing, to reveal non-broadcasting vessels and monitoring offshore development around the world.
Before joining Global Fishing Watch, Paolo was a postdoctoral scholar at the NASA Jet Propulsion Laboratory, where he used radar and laser satellite measurements to quantify ice sheet loss and sea level change. In 2016, he received the NASA Most Valuable Player Award for research in cryospheric sciences, followed by two Group Achievement Awards for his contribution to the ICESat-2 satellite mission in 2020. In his early career, Paolo participated in several scientific cruises to the Southern Ocean, including an expedition to Antarctica.
Paolo obtained his doctorate in geophysics from the University of California, San Diego, and has authored numerous articles on climate research using statistical and machine learning methods.